2006Functional EcologyRequires access

Net assimilation rate, specific leaf area and leaf mass ratio: which is most closely correlated with relative growth rate? A meta‐analysis

Bill Shipley

Open publisher page 321 citations

Abstract

Summary Data were compiled consisting of 1240 observations (614 species) from 83 different experiments published in 37 different studies, in order to quantify the relative importance of net assimilation rate (NAR, g cm −2 day −1 ), specific leaf area (SLA, cm 2 g −1 ) and leaf mass ratio (LMR, g g −1 ) in determining relative growth rate (RGR, g g −1 day −1 ), and how these change with respect to daily quantum input (DQI, moles m −2 day −1 ) and growth form (herbaceous or woody). Each of ln(NAR), ln(SLA) and ln(LMR) were separately regressed on ln(RGR) using mixed model regressions in order to partition the between‐experiment and within‐experiment variation in slopes and intercepts. DQI and plant type were then added to these models to see if they could explain some of the between‐experiment variation in the relative importance of each growth component. LMR was never strongly related to RGR. In general, NAR was the best general predictor of variation in RGR. However, for determining RGR the importance of NAR decreased, and the importance of SLA increased, with decreasing daily quantum input in experiments containing herbaceous species. This did not occur in experiments involving woody species.

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What this paper is about

Summary Data were compiled consisting of 1240 observations (614 species) from 83 different experiments published in 37 different studies, in order to quantify the relative importance of net assimilation rate (NAR, g cm −2 day −1 ), specific leaf area (SLA, cm 2 g −1 ) and leaf mass ratio (LMR, g g −1 ) in determining relative growth rate (RGR, g g −1 day −1 ), and how these change with respect to daily quantum input (DQI, moles m −2 day −1 ) and growth form (herbaceous or woody). Each of ln(NAR), ln(SLA) and ln(LMR) were separately regressed on ln(RGR) using mixed model regressions in order to partition the between‐experiment and within‐experiment variation in slopes and intercepts. DQI and plant type were then added to these models to see if they could explain some of the between‐experiment variation in the relative importance of each growth component. LMR was never strongly related to RGR. In general, NAR was the best general predictor of variation in RGR. However, for determining RGR the importance of NAR decreased, and the importance of SLA increased, with decreasing daily quantum input in experiments containing herbaceous species. This did not occur in experiments involving woody species.

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Available abstract

Summary Data were compiled consisting of 1240 observations (614 species) from 83 different experiments published in 37 different studies, in order to quantify the relative importance of net assimilation rate (NAR, g cm −2 day −1 ), specific leaf area (SLA, cm 2 g −1 ) and leaf mass ratio (LMR, g g −1 ) in determining relative growth rate (RGR, g g −1 day −1 ), and how these change with respect to daily quantum input (DQI, moles m −2 day −1 ) and growth form (herbaceous or woody). Each of ln(NAR), ln(SLA) and ln(LMR) were separately regressed on ln(RGR) using mixed model regressions in order to partition the between‐experiment and within‐experiment variation in slopes and intercepts. DQI and plant type were then added to these models to see if they could explain some of the between‐experiment variation in the relative importance of each growth component. LMR was never strongly related to RGR. In general, NAR was the best general predictor of variation in RGR. However, for determining RGR the importance of NAR decreased, and the importance of SLA increased, with decreasing daily quantum input in experiments containing herbaceous species. This did not occur in experiments involving woody species.

Key concepts: Relative growth rate, Herbaceous plant, Specific leaf area, Biology, Growth rate, Botany, Animal science, Horticulture

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